Surface Defects Detection of PVC Cards by Using Machine Vision

• Main Authors: Shi-Qing Xu, 許世清
• Other Authors: Ming-Chuan Wu
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/6utr2e

碩士 === 國立臺北科技大學 === 製造科技研究所 === 95 === In order to solve the problem that defects arise in the quality control step. This study develops a system to inspect PVC card’s surface defects of three kinds of colors by using machine vision. During the manufacturing process of PVC cards, the defects are generated because of the painting machine and artificial neglect. In this study, the types of defect are inaccurate size, flashes, scratches, spots, bubbles and pollution. This study divided into two steps, including hardware establishment and image processing. Because of the high reflecting surface of the PVC cards, we can not acquire image totally and show the defects, and it’s meaningless to other process. Therefore, applies dark-field imaging technique to capture images to solve the problem. It is divided into pattern matching and surface defect detection. In the pattern matching, we applied the Blob method to extract the characteristic of the words, and we used Euclidean distance to match the characteristics, recorded the position of the word. As to the pattern, we take two phase search method and three step search algorithm to find the similar block, record the position after pattern matching. This study take histogram equalization to enhance contrast of surface defect, shift the block adaptive filter and use statistical control limits to intensify the low-contrast abnormal point. Experimental results have shown that the proposed method can effectively detect small defects on low-contrast surface. The average accuracy of inspection is 92.7%, and the average detection time is 0.25~0.31 seconds. In this study, we can improve the drawbacks of human vision inspection on detecting the low-contrast surface defects.